We propose a joint distribution adaptation network (JDAN) model for multi-source EEG-based emotion recognition.

Dec 27, 2021 · Electroencephalogram (EEG)-based emotion recognition is a feasible method to improve human-robot interaction (HRI) systems.

Sep 16, 2024 · The JMMD has been investigated in [140] as part of the loss function for a DNN in an Emotion Recognition task. Instead, the authors of [141] ...

Sep 14, 2022 · This paper proposes a novel multi-source joint domain adaptation (MSJDA) network. We first map all domains to a shared feature space and then align the joint ...

Sep 15, 2022 · This paper proposes a novel multi-source joint domain adaptation (MSJDA) network. We first map all domains to a shared feature space and then align the joint ...

We propose a novel emotion recognition method based on Multi-Source Domain Branch Self-Selected Joint Domain Adaptation (MSS-JDA).

Oct 31, 2024 · Method: This study introduces a multi-source domain adaptation common- branch network for EEG emotion recognition and proposes a novel sample.

The joint distribution adaptation method [38] approximates the joint distribution by adapting both the marginal and conditional distributions. By making use of ...

Focusing on cross-subject or cross-dataset automated emotion recognition with EEG features, we propose in this article a robust multi-source co-adaptation ...

Joint Distribution Adaptation Network for Multi-source Electroencephalogram-based Emotion Recognition. Ying Tan, Gan Liu, Lingfeng Chen, Zhe Sun, Feng Duan.